Head-to-head
GPT-5.5 vs Gemini 3 Pro: which AI model wins in 2026?
GPT-5.5 ($30/1M out) and Gemini 3 Pro ($12/1M out (prompts ≤200K)) are two of the most-used AI models in 2026. Across 6 community votes, GPT-5.5 leads with 57% approval.
Quick verdict
On Reasoning, pick GPT-5.5: the arena rates it 5/5 against 4.5/5 for Gemini 3 Pro. On budget, Gemini 3 Pro wins: it starts at $12/1M out (prompts ≤200K) versus $30/1M out for GPT-5.5.
Line-by-line comparison
Strengths and weaknesses
GPT-5.5
- 1M-token context window (1,050,000) with 128K max output and reasoning effort tunable from none to xhigh
- State-of-the-art ARC-AGI-2 at 85.0% (vs 73.3% for GPT-5.4) and Terminal-Bench 2.0 at 82.7%
- Strong agentic coding autonomy: devs report it one-shots tasks that took GPT-5.4 multiple turns and fixes its own mistakes; +50 points on Code Arena vs GPT-5.4
- Aggressive discounts: 90% off cached input ($0.50/1M) and 50% off via Batch or Flex ($2.50/$15)
- Fast for a frontier reasoner: devs say it is the first GPT model comfortable to run at medium or low thinking effort
- List price doubled vs GPT-5.4 ($5/$30 vs $2.50/$15) for the same 1M-token context window
- Overly literal instruction-following: devs report it fails to infer intent in obvious places where Claude succeeds
- Trails Claude Opus 4.8 on SWE-bench Pro (58.6% vs 69.2%); HN developers still favor Claude roughly 2:1 for coding
- Sometimes too conservative with code changes or skips deep reasoning entirely, answering immediately on complex prompts
- Long-context surcharge: prompts over 272K input tokens are billed 2x input and 1.5x output for the whole session
Gemini 3 Pro
- Topped LMArena at launch with a record 1501 Elo and scored 91.9% on GPQA Diamond, state of the art at release
- ARC-AGI-2 at 31.1%, roughly 6x Gemini 2.5 Pro (4.9%) and nearly double GPT-5.1 (17.6%) at the time
- Best-in-class multimodal understanding: 81% MMMU-Pro, 87.6% Video-MMMU, with a 1M-token context window
- Strong agentic coding: 76.2% SWE-bench Verified, 54.2% Terminal-Bench 2.0, 1487 Elo on WebDev Arena
- Undercut rivals on price at $2/$12 per 1M tokens, below Claude Sonnet-class pricing ($3/$15)
- Configurable thinking_level (low/medium/high) lets developers trade reasoning depth against latency and cost
- Overconfident hallucinations: on AA-Omniscience it gave a wrong answer 88% of the time instead of declining, vs 48% for Claude Sonnet 4.5 (the-decoder)
- Sycophancy widely reported by reviewers (Zvi Mowshowitz: 'vast intelligence with no spine'); needs tight system prompts
- Tool-calling reliability issues in agent stacks: devs reported tool outputs dumped into the chat thread and more scaffolding needed than OpenAI/Anthropic models
- Slow at high thinking level: time to first token measured around 30-60s on AI Studio despite ~130 tok/s output speed
- Retired: shut down on the Gemini API and AI Studio on March 9, 2026, with gemini-3-pro-preview now aliased to Gemini 3.1 Pro
Cast your verdict
One recommendation per tool per gladiator. It reshapes the crowd score everyone sees.
The arena’s verdict on GPT-5.5
Pick GPT-5.5 over GPT-5.4 if you need stronger agentic autonomy, terminal-heavy workflows, or SOTA abstract reasoning, but know the list price doubled from GPT-5.4's $2.50/$15 to $5/$30 while the 1M-token context stayed the same. Teams doing high-stakes multi-file refactoring may still prefer Claude Opus, which leads SWE-bench Pro (69.2% vs 58.6%) and infers intent better from loose prompts. Budget-sensitive users should mind the 272K-token surcharge and reports of faster limit burn, and lean on caching, Batch, or Flex to halve costs.
The arena’s verdict on Gemini 3 Pro
A landmark release that put Google back on top in late 2025, with a huge reasoning jump over Gemini 2.5 Pro and the best multimodal scores of its generation. As of mid-2026 there is no reason to choose it: Google shut it down on the API on March 9, 2026, and Gemini 3.1 Pro costs exactly the same while more than doubling ARC-AGI-2 performance (77.1% vs 31.1%). Teams on legacy deployments should migrate to 3.1 Pro, which the old model ID now points to anyway. Avoid it for hallucination-sensitive workloads unless you add grounding, a weakness reviewers flagged repeatedly.
What the crowd says
On GPT-5.5
“It is painfully literal. Where Claude infers intent in obvious places, 5.5 wants everything spelled out. And the price doubled vs 5.4 for the same 1M context.”
“85 on ARC-AGI-2 and you can feel it. Stuff that used to stall my agent just resolves now. 1M context with 128K output covers every workflow I have.”
“5.5 one-shots tasks that took 5.4 three turns, and it fixes its own mistakes mid-run instead of doubling down. The reasoning effort dial from none to xhigh is genuinely useful.”
On Gemini 3 Pro
“Confidently wrong is its worst mode. On AA-Omniscience it gave a wrong answer 88% of the time instead of declining. Add the sycophancy and you need a tight system prompt to trust it.”
“ARC-AGI-2 at 31% was about 6x Gemini 2.5 Pro and nearly double GPT-5.1 at the time. For visual-heavy work (81 MMMU-Pro) nothing else came close.”
“1501 Elo on LMArena at launch was deserved. Multimodal is where it kills, I feed it lecture videos and dense PDFs and it just gets it. 1M context helps.”
Keep comparing
Frequently asked questions
Is GPT-5.5 better than Gemini 3 Pro?
On Reasoning, GPT-5.5 rates higher (5/5 vs 4.5/5). The right pick depends on your use case. The line-by-line comparison on this page breaks down pricing, key specs and arena ratings.
Which is cheaper, GPT-5.5 or Gemini 3 Pro?
Gemini 3 Pro is cheaper: it starts at $12/1M out (prompts ≤200K), while GPT-5.5 starts at $30/1M out.
How much do GPT-5.5 and Gemini 3 Pro cost per 1M tokens?
GPT-5.5: $5/1M in per 1M input tokens, $30/1M out per 1M output tokens. Gemini 3 Pro: $2/1M in (prompts ≤200K) per 1M input tokens, $12/1M out (prompts ≤200K) per 1M output tokens.